Software for Genome‐Wide Association Studies in Autopolyploids and Its Application to Potato. Issue 2 (1st July 2016)

• Record Type: Journal Article
• Authors: Rosyara, Umesh R.; De Jong, Walter S.; Douches, David S.; Endelman, Jeffrey B.
• Is Part Of: œplant genome. Volume 9:Issue 2(2016)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-07-01
• Subjects: Plant genomes -- Periodicals; Plant genome mapping -- Periodicals; 572.862
• DOI: 10.3835/plantgenome2015.08.0073
• Languages: English
• ISSNs: 1940-3372

Abstract

Abstract : Genome‐wide association studies (GWAS) are widely used in diploid species to study complex traits in diversity and breeding populations, but GWAS software tailored to autopolyploids is lacking. The objectives of this research were to (i) develop an R package for autopolyploids based on the Q + K mixed model, (ii) validate the software with simulated data, and (iii) analyze a diversity panel of tetraploid potatoes. A unique feature of the R package, called GWASpoly, is its ability to model different types of polyploid gene action, including additive, simplex dominant, and duplex dominant. Using a simulated tetraploid population, we confirmed our hypothesis that statistical power is higher when the assumed gene action in the GWAS model matches the gene action at unobserved quantitative trait loci (QTL). Thirteen traits were analyzed in the Solanaceae Coordinated Agricultural Project (SolCAP) potato diversity panel and, consistent with previous studies, significant QTL for tuber shape and eye depth co‐localized on chromosome 10. For the other traits, only marginally significant QTL were detected, most likely due to insufficient statistical power: for simulated traits with a heritability ( h 2 ) of 0.3, the median genome‐wide power was only 0.01. Our results indicate that both marker density and population size were limiting factors for GWAS with the SolCAP panel.